AI Cloud Integration: Next-Gen Strategies for Innovation
- SK Bioscience has spent the last three years (2022-2024) constructing a robust digital infrastructure to support future Artificial Intelligence (AI) initiatives.
- Security was a key consideration, with systemized authentication, authorization, and authority management for all Application Programming Interfaces (APIs).
- Manager Young-gyun Yoon emphasized that this integrated strategy and the webMethods-based linkage structure represent a core component of SK Bioscience's long-term digital infrastructure strategy.
SK Bioscience builds AI-Driven Management System on New Digital Infrastructure
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Figure 2. SK Bioscience’s webMethods interface method
SK Bioscience
Foundation for AI: core Systems Established 2022-2024
SK Bioscience has spent the last three years (2022-2024) constructing a robust digital infrastructure to support future Artificial Intelligence (AI) initiatives. This groundwork includes the implementation of S/4 HANA, a webMethods-based interface platform, a data lake, Robotic Process Automation (RPA) and cloud infrastructure, and integrated systems for Learning Management (LMS), Electronic Document Management (EDMS), and Quality Management (QMS).
Security was a key consideration, with systemized authentication, authorization, and authority management for all Application Programming Interfaces (APIs). A dedicated gateway was also established to monitor logs and traffic for external system connections, alongside a comprehensive audit system.
dCQSS: Moving Beyond Algorithms to Data-Driven Decisions
Building on this infrastructure, SK Bioscience is developing an AI-based management habitat, termed dCQSS. The focus is not solely on AI algorithm growth, but on creating a decision-making structure based on the seamless interconnection of enterprise systems and real-time data flow. According to Manager Young-gyun Yoon,realizing business value from digital infrastructure requires a data-based architecture,and SK Bioscience is now actively pursuing this.
Three pillars of AI Utilization within dCQSS
SK Bioscience’s dCQSS is designed as a strategic management model offering integrated data access and AI tools to enhance productivity across the organization. The company has defined three key areas for AI utilization:
- Analytics AI: Empowering all employees to analyze data and inform decision-making.
- Generative AI: Automating and increasing efficiency in repetitive tasks.
- Expert AI: Providing bio experts with advanced scientific analysis capabilities.